Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2

Abstract

The functional connectome of the human brain comprises time-varying network structure that facilitates efficient inter-module communication and support flexible cognitive functions. However, little is known about how the connectome dynamics of the brain emerges and develops at very early stages of human life and whether this dynamics is predictive of neurocognitive outcomes later in life. Here, we employed resting-state functional MRI data from 39 infants (31 to 42 postmenstrual weeks) and a multilayer network model to characterize the development of connectome dynamics during the third trimester and its critical role in predicting future neurocognitive outcomes at 2 years of age. We observed that the modular architecture of baby functional connectomes spontaneously reconfigures over time, with lower network module switching across time primarily in the primary regions and higher module switching mainly in the association areas. With development, the dynamic switching between the brain modules was significantly decreased, primarily located in the lateral precentral gyrus, medial temporal lobe, and subcortical areas. The clustering analysis further revealed that the primary areas displayed a higher developmental rate than the higher-order systems. Using the support vector regression approach, we found that brain connectome dynamics at birth significantly predicted cognitive and language performance at 2 years of age. Our findings highlight the emergence and spatially inhomogeneous maturation of the neonate connectome dynamics, laying a critical neural foundation for the development of cognitive and language skills later in life.